Any efficient way to compare two dataframes and append new entries in pandas?

I have new files which I want to add them to historical table, before that, I need to check new file with historical table by comparing its two column in particular, one is state and another one is date column. First, I need to check max (state, date), then check those entries with max(state, date) in historical table; if they are not historical table, then append them, otherwise do nothing. I tried to do this in pandas by group-by on new file and historical table and do comparison, if any new entries from new file that not in historical data, then add them. Now I have issues to append new values to historical table correctly in pandas. Does anyone have quick thoughts?

My current attempt:

import pandas as pd 
  
src_df=pd.read_csv("https://raw.githubusercontent.com/adamFlyn/test_rl/main/src_df.csv")
hist_df=pd.read_csv("https://raw.githubusercontent.com/adamFlyn/test_rl/main/historical_df.csv")
picked_rows = src_df.loc[src_df.groupby('state')['yyyy_mm'].idxmax()]

I want to check picked_rows in hist_df where I need to check by state and yyyy_mm columns, so only add entries from picked_rows where state has max value or recent dates. I created desired output below. I tried inner join or pandas.concat but it is not giving me correct out. Does anyone have any ideas on this?

Here is my desired output that I want to get:

import pandas as pd
desired_output=pd.read_csv("https://raw.githubusercontent.com/adamFlyn/test_rl/main/output_df.csv")

enter image description here

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